Related papers: A Machine Learning Based Morphological Classificat…

Remnant radio galaxies represent the dying phase of radio-loud active galactic nuclei (AGN). Large samples of remnant radio galaxies are important for quantifying the radio galaxy life cycle. The remnants of radio-loud AGN can be identified…

Context. Active galactic nuclei (AGNs) and star forming galaxies (SFGs) are the primary sources of extragalactic radio sky. But it is difficult to distinguish the radio emission produced by AGNs from that by SFGs, especially when the radio…

Machine learning techniques have been increasingly used in astronomical applications and have proven to successfully classify objects in image data with high accuracy. The current work uses archival data from the Faint Images of the Radio…

We present the application of deep machine learning technique to classify radio images of extended sources on a morphological basis using convolutional neural networks. In this study, we have taken the case of Fanaroff-Riley (FR) class of…

Basing our analysis on ROGUE I, a catalog of over 32,000 radio sources associated with optical galaxies, we provide two diagnostics to select the galaxies where the radio emission is due to an active galactic nucleus (AGN). Each of these…

Radio-loud active galaxies (RLAGN) can exhibit various morphologies. The Fanaroff-Riley (FR) classifications, which are defined by the locations of peaks in surface brightness, have been applied to many catalogues of RLAGN. The FR…

We present an independent catalog (FRIIRGcat) of 45,241 Fanaroff-Riley Type II (FR-II) radio galaxies compiled from the Very Large Array Faint Images of the Radio Sky at Twenty-centimeters (FIRST) survey and employed the deep learning…

We present the largest visually selected sample of extended ($>$60 arcsec) radio-loud active galactic nuclei (RLAGN) to date, based on the LOw-Frequency Array Two-Metre Sky Survey second data release (LoTSS DR2). From the broader LoTSS DR2…

The continuum emission from radio galaxies can be generally classified into different morphological classes such as FRI, FRII, Bent, or Compact. In this paper, we explore the task of radio galaxy classification based on morphology using…

We investigate the optical morphologies of candidate active galaxies identified at radio, X-ray, and mid-infrared wavelengths. We use the Advanced Camera for Surveys General Catalog (ACS-GC) to identify 372, 1360, and 1238 AGN host galaxies…

The morphology of a radio galaxy is highly affected by its central active galactic nuclei (AGN), which is studied to reveal the evolution of the super massive black hole (SMBH). In this work, we propose a morphology generation framework for…

The faint radio-source population includes sources dominated both by star formation and active galactic nuclei (AGN), encoding the evolution of activity in the Universe. To investigate its nature, we probabilistically classified 4,471 radio…

We present a machine learning model to classify Active Galactic Nuclei (AGN) and galaxies (AGN-galaxy classifier) and a model to identify type 1 (optically unabsorbed) and type 2 (optically absorbed) AGN (type 1/2 classifier). We test…

We conducted an extensive identification and analysis of various morphological classes and subclasses of radio galaxies using the latest high-resolution data from the second data release of the LOFAR Two-Metre Sky Survey (LoTSS DR2). This…

Modern radio telescope surveys, capable of detecting billions of galaxies in wide-field surveys, have made manual morphological classification impracticable. This applies in particular when the Square Kilometre Array Observatory (SKAO)…

We present a study of the extended radio emission in a sample of 8434 low redshift (z < 0.35) broad line active galactic nuclei (AGN) from the Sloan Digital Sky Survey (SDSS). To calculate the jet and lobe contributions to the total radio…

The Fermi Gamma-ray Space Telescope is producing the most detailed inventory of the gamma-ray sky to date. Despite tremendous achievements approximately 25% of all Fermi extragalactic sources in the Second Fermi LAT Catalogue (2FGL) are…

We present a kinematic analysis based on the large Integral Field Spectroscopy (IFS) dataset of SDSS-IV MaNGA (10.000 galaxies). We have compiled a diverse sample of 594 unique Active Galactic Nuclei (AGN), identified through a variety of…

The second Fermi-LAT source catalog (2FGL) is the deepest all-sky survey available in the gamma-ray band. It contains 1873 sources, of which 576 remain unassociated. Machine-learning algorithms can be trained on the gamma-ray properties of…

The relative positions of the high and low surface brightness regions of radio-loud active galaxies in the 3CR sample were found by Fanaroff and Riley to be correlated with their luminosity. We revisit this canonical relationship with a…